105 citations · 149 across the 21 of their papers we have counts for
9 papers · 1 filter
LVLM-Compress-Bench: Benchmarking the Broader Impact of Large Vision-Language Model Compression
Souvik Kundu, Anahita Bhiwandiwalla, Sungduk Yu +6
Despite recent efforts in understanding the compression impact on large language models (LLMs) in terms of their downstream task performance and trustworthiness on relatively simpl…
ClimDetect: A Benchmark Dataset for Climate Change Detection and Attribution
Sungduk Yu, Brian L. White, Anahita Bhiwandiwalla +6
Detecting and attributing temperature increases driven by climate change is crucial for understanding global warming and informing adaptation strategies. However, distinguishing hu…
Uncovering Bias in Large Vision-Language Models at Scale with Counterfactuals
Phillip Howard, Kathleen C. Fraser, Anahita Bhiwandiwalla +1
With the advent of Large Language Models (LLMs) possessing increasingly impressive capabilities, a number of Large Vision-Language Models (LVLMs) have been proposed to augment LLMs…
LVLM-Interpret: An Interpretability Tool for Large Vision-Language Models
Gabriela Ben Melech Stan, Estelle Aflalo, Raanan Yehezkel Rohekar +7
In the rapidly evolving landscape of artificial intelligence, multi-modal large language models are emerging as a significant area of interest. These models, which combine various…
Uncovering Bias in Large Vision-Language Models with Counterfactuals
Phillip Howard, Anahita Bhiwandiwalla, Kathleen C. Fraser +1
With the advent of Large Language Models (LLMs) possessing increasingly impressive capabilities, a number of Large Vision-Language Models (LVLMs) have been proposed to augment LLMs…
SocialCounterfactuals: Probing and Mitigating Intersectional Social Biases in Vision-Language Models with Counterfactual Examples
Phillip Howard, Avinash Madasu, Tiep Le +3
While vision-language models (VLMs) have achieved remarkable performance improvements recently, there is growing evidence that these models also posses harmful biases with respect…
Analyzing Zero-Shot Abilities of Vision-Language Models on Video Understanding Tasks
Avinash Madasu, Anahita Bhiwandiwalla, Vasudev Lal
Foundational multimodal models pre-trained on large scale image-text pairs or video-text pairs or both have shown strong generalization abilities on downstream tasks. However unlik…
ManagerTower: Aggregating the Insights of Uni-Modal Experts for Vision-Language Representation Learning
Xiao Xu, Bei Li, Chenfei Wu +6
Two-Tower Vision-Language (VL) models have shown promising improvements on various downstream VL tasks. Although the most advanced work improves performance by building bridges bet…
Using Scene Graph Context to Improve Image Generation
Subarna Tripathi, Anahita Bhiwandiwalla, Alexei Bastidas +1
Generating realistic images from scene graphs asks neural networks to be able to reason about object relationships and compositionality. As a relatively new task, how to properly e…